Abstract
Models of correct recognition algorithms are considered that are based on incorrect logical regularities called logical correctors. A new model of a logical corrector is constructed. The results of testing this model on real data are presented.
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This article uses the materials of the report submitted at the 11th International Conference “Pattern Recognition and Image Analysis: New Information Technologies,” Samara, The Russian Federation, September 23–28, 2013.
Elena Vsevolodovna Djukova. Born 1945. Doctor in physics and mathematics. Currently is a chief researcher at the Dorodnicyn Computing Centre, Russian Academy of Sciences. Scientific interests: logical data analysis, pattern recognition, discrete mathematics, logical recognition procedures, computational complexity of discrete problems, logical recognition procedures, computational complexity of discrete problems, and synthesis of asymptotically optimal algorithms for solving discrete problems.
Mariya Mikhailovna Lyubimtseva. Born 1991. Graduated from secondary school no. 1360 in Moscow. Currently is a fifth-year student at the Faculty of Computational Mathematics and Cybernetics, Moscow State University. Scientific interests: pattern recognition, logical recognition procedures, image classification, and computer vision.
Petr Aleksandrovich Prokofjev. Born 1982. Graduated from the Faculty of information Security, Institute of Cryptography, Telecommunications and Computer Science in 2005. Scientific interests: methods of pattern recognition, analysis of texts, mathematical programming, and discrete methods of data analysis.
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Djukova, E.V., Lyubimtseva, M.M. & Prokofjev, P.A. Logical correctors in recognition. Pattern Recognit. Image Anal. 24, 358–364 (2014). https://doi.org/10.1134/S1054661814030031
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DOI: https://doi.org/10.1134/S1054661814030031